Adapt

The National Science Foundation funds over seven billion dollars of research annually, nearly all of which relies heavily on information technology. The digital data produced and computing systems used by that research are subject to the same risks as other data and computing systems on the Internet. Appropriate cybersecurity is necessary both to make today's scientific discoveries possible and to ensure that the science is trustworthy. However, NSF science is often necessarily performed in open, collaborative environments that span organizational and national boundaries.

The cyber security threat to organizations and governments has continued to grow with increasing dependence on information technology; meanwhile, the entities behind cyber attacks increase in sophistication. Cyber security professionals, the individuals responsible for keeping organizations secure, investigate network activity to find, identify, and respond to threats. These individuals are among the last lines of defense for an organization. Cyber security professionals depend on automated tools to perform their jobs but must make critical decisions that impact security.

This project focuses on tackling the security and privacy of Cyber-Physical Systems (CPS) by integrating the theory and best practices from the information security community as well as practical approaches from the control theory community. The first part of the project focuses on security and protection of cyber-physical critical infrastructures such as the power grid, water distribution networks, and transportation networks against computer attacks in order to prevent disruptions that may cause loss of service, infrastructure damage or even loss of life.

Social networking and sensor-rich devices such as smartphones are becoming increasingly pervasive in today's society. People can share information concerning their location, activity, fitness, and health with their friends and family while benefiting from applications that leverage such information. Yet, users already find managing their privacy to be challenging, and the complexity involved in doing so is bound to increase.

The project develops new technologies for continual, web-scale measurement and rapid defenses against emerging threats to web privacy and security arising from third-party tracking. It draws from the fields of web security, systems, measurement, statistics, and machine learning. The outputs of this project will enable website administrators to find and fix a large class of privacy and security problems. They will help improve existing browser privacy tools.